This is a shiny application for Mass Spectrometry (Proteomics) lab at Charles Perkins Centre in University of Sydney.
README.md file (https://github.com/taiyunkim/QCMAP#212-database) or here in this documentallFeatures.csv) into your working directory.app.Rhttp://shiny.maths.usyd.edu.au/QCMAP/
This tab shows historical overview of your instrument performance.
This tab is used to predict quality of your experimental sample
Screenshot of Prediction tab using example data
This tab is used to generate CSV (database) file for your application.
You will need to have database (CSV file) named allFeatures.csv that contains summary of the features, instrument details, filenames and dates. An example of the file headers and data is shown below.
alt text
NOTE: Make sure that the order of your headers are identical to the screenshot provided.
This can be generated using the [R script provided OR “Database” tab of the application at http://shiny.maths.usyd.edu.au/QCMAP/]. In order to create this file from multiple MaxQuant output files, zip the output files by studies and upload multiple zip files to combine them all together to one CSV file.
For example, given a file structure as follows,
./
├── study1
│ ├── Oxidation\ (M)Sites.txt
│ ├── aifMsms.txt
│ ├── allPeptides.txt
│ ├── evidence.txt
│ ├── libraryMatch.txt
│ ├── matchedFeatures.txt
│ ├── modificationSpecificPeptides.txt
│ ├── ms3Scans.txt
│ ├── msScans.txt
│ ├── msms.txt
│ ├── msmsScans.txt
│ ├── mzRange.txt
│ ├── parameters.txt
│ ├── peptides.txt
│ ├── proteinGroups.txt
│ ├── summary.txt
│ └── tables.pdf
└── study2
├── Oxidation\ (M)Sites.txt
├── aifMsms.txt
├── allPeptides.txt
├── evidence.txt
├── libraryMatch.txt
├── matchedFeatures.txt
├── modificationSpecificPeptides.txt
├── ms3Scans.txt
├── msScans.txt
├── msms.txt
├── msmsScans.txt
├── mzRange.txt
├── parameters.txt
├── peptides.txt
├── proteinGroups.txt
├── summary.txt
└── tables.pdf
Compress study1 and study2 as separate zip files as input.